We are seeking an experienced Snowflake Python Developer with a strong background in Data Warehousing (DWH), ETL, and Big Data technologies. The ideal candidate will have deep hands-on experience in Python/PySpark, Snowflake Data Cloud, and SQL/PL-SQL, along with strong analytical and performance optimization skills.

You will play a key role in designing, developing, and maintaining scalable, efficient, and secure data pipelines and ETL processes to support analytics, business intelligence, and data science initiatives.

Key Responsibilities :

- Design, develop, and implement ETL pipelines to extract, transform, and load data from diverse data sources into Snowflake.

- Develop data ingestion and data transformation scripts using Python and PySpark.

- Create and optimize Snowflake SQL scripts, stored procedures, and user-defined functions (UDFs) for data transformation and validation.

- Implement and maintain data integration workflows across Snowflake, Oracle, and other source systems.

- Perform data modeling, schema design, and data partitioning for efficient querying and storage in Snowflake.

- Conduct performance tuning for SQL queries, ETL jobs, and data pipelines.

- Optimize Snowflake compute and storage costs through best practices and resource monitoring.

- Identify and resolve performance bottlenecks in ETL processes and database operations.

- Develop automation scripts using Python, Unix shell scripting, and orchestration tools for scheduling and monitoring ETL workflows.

- Integrate Snowflake with external data sources, APIs, or third-party systems.

- Implement error handling, logging, and alerting mechanisms for pipeline monitoring.

- Work closely with data architects, business analysts, and BI developers to ensure data accuracy and consistency.

- Collaborate with cross-functional teams to design end-to-end data solutions.

- Maintain detailed documentation for ETL processes, data mappings, and database structures.

- Support production deployments, troubleshooting, and root cause analysis.

Required Skills & Experience :

Technical Skills :

Programming Languages :

- Strong hands-on experience with Python and PySpark.

Data Warehousing :

- Deep understanding of DWH concepts, ETL methodologies, and data modeling techniques (star/snowflake schema).

- Proven expertise with Snowflake (SnowSQL, Streams, Tasks, Time Travel, Cloning, etc.).

- Advanced proficiency in Oracle SQL/PL-SQL and performance tuning of complex queries.

- Experience with Unix shell scripting for workflow automation.

- Familiarity with ETL orchestration or data pipeline tools such as Airflow, Informatica, Talend, or Azure Data Factory (nice to have).

- Proficiency with Git and CI/CD integration for data pipelines.

- Exposure to AWS, Azure, or GCP cloud data services.